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Challenges the testing industry to change its methods and approaches aggressively to meet industry′s needs as we move towards the twenty‐first century. While the training and development field has addressed the critical issues of empowerment, quality, teamwork, etc., the testing industry remains basically in the Dark Ages, continuing to rely on archaic paper and pencil tests which have little to do with such concepts as teamwork, etc. Addresses testing as the first step leading to a competent workforce. Discusses trends which will have an impact on testing, e.g. movement towards team‐oriented work environments. Then discusses the impact of these trends in creating challenges for the testing industry – tests will be needed which can be used not only for selecting people, but also for providing diagnostic developmental information (given labour shortages, it will be critical to point out to those people hired as well as the organization, how these people can improve their skills so as to increase the likelihood of their being successful on‐the‐job performers). Contrasts innovative testing approaches, e.g. video‐based testing, with more conventional methods in terms of meeting the challenges.

To determine the status of internet and e‐commerce adoption by the Taiwan semiconductor industry, the research is designed to help government and enterprise in formulating strategic plans and making resource allocation decisions.

Using the three‐level model of internet commerce adoption (MICA), a survey of 287 companies and web sites was designed. Semiconductor firms were placed into five categories: integrated circuit (IC) design, manufacturing, packaging, IC testing, and peripheral device manufacturing.

The MICA model shows the internet adoption ratio for semiconductor firms as 82.6 percent, significantly higher than the electronics and electrical machinery industry sector (56.5 percent). The IC manufacturing and packaging segment are in the processing stage, the final stage of development for the MICA model. One‐third of the IC testing industry segment falls into the provision stage, and 36.1 percent web sites are in the processing stage. The IC design and peripherals industrial segments are located in the provision stage.

The IC manufacturing segment is conducting more financial transactions than the other segments – a result that matches earlier research showing that larger companies are most likely to implement e‐business applications. Many enterprises in the industry are lagging with the adoption of the internet indicating a need for education and training.

This benchmark study provides a framework for evaluating the internet adoption status of semiconductor and other high technology firms. The MICA model is demonstrated to be suitable for evaluating the different stages of internet adoption.

The following is an introductory profile of the fastest growing firms over the three-year period of the study listed by corporate reputation ranking order. The business activities in which the firms are engaged are outlined to provide background information for the reader.

In early 2014, recent Stanford University graduate Tyler Shultz was in a quandary. He had been working at Theranos, a blood-diagnostic company founded by Elizabeth Holmes, a Stanford-dropout wunderkind, for almost a year. Shultz had learned enough about the company to realize that its practices and the efficacy of its much-touted finger-prick blood-testing technology were questionable and that the company was going to great lengths to hide this fact from the public and from regulators.

Theranos and Holmes were Silicon Valley darlings, enjoying positive press and lavish attention from potential investors and technology titans alike. Just as companies like PayPal had revolutionized the stagnant payments industry and Uber had upended the for-hire transportation sector, Theranos had been positioned as the latest technology firm to substantially disrupt yet another mature sector: the medical laboratory business. By the start of 2014, the company had raised more than $400 million in funding, and had an estimated market valuation of $9 billion.

Shultz's situation was exacerbated by the fact that his grandfather, the highly respected former US Secretary of State George Shultz, was on the Theranos board and was one of Elizabeth Holmes's biggest supporters.

But Tyler Shultz worried about the customers he was convinced were receiving highly unreliable and often inaccurate blood-test results. With so much at stake, Shultz wondered how he should proceed. Should he raise his concerns with the firm's investors? Blow the whistle externally? Report to industry regulators? Go away quietly?

This case and its subsequent four brief follow-up cases are based largely on interviews with Tyler Shultz, and outline the dilemma he faced and the various steps he would take both to extricate himself from his unsavory position and let the public know the full extent of the deception at Theranos.

Five optional handouts are available to instructors to further discussion after the case has been debriefed. The handouts serve as additional decision points for the students if your class time permits.

This study aims to develop a parsimonious model to estimate US aggregate hotel industry revenue using domestic trips, consumer confidence index, international inbound trips, personal consumption expenditure and number of hotel rooms as predictor variables. Additionally, the study applied the model in six sub-segments of the hotel industry – luxury, upper upscale, upscale, upper midscale, midscale and economy.

Using monthly aggregate data from the past 22 years, the study adopted the auto-regressive distribute lags (ARDL) approach in developing the estimation model. Unit root analysis and cointegration test were further utilized. The model showed significant utility in accurately estimating aggregate hotel industry and sub-segment revenue.

All predictor variables except number of rooms showed significant positive influences on aggregate hotel industry revenue. Substantial variations were noted regarding estimating sub-segment revenue. Consumer confidence index positively affected all sub-segment revenues, except for upper upscale hotels. Inbound trips by international tourists and personal consumption expenditure positively influenced revenue for all sub-segments but economy hotels. Domestic trips by US residents added significant explanatory power to only upper upscale, upscale and economy hotel revenue. Number of hotel rooms only had significant negative effect on luxury and upper upscale hotel sub-segment revenues.

Hotel operators can make marketing and operating decisions regarding pricing, inventory allocation and strategic management based on the revenue estimation models specific to their segments.

It is the first study that adopted the ARDL bound approach and analyzed the predictive capacity of macroeconomic variables on aggregate hotel industry and sub-segment revenue.

The resource-based view (RBV) of the firm focuses on how firm-level assets and capabilities influence firm performance. Scholars have noted the need for studies grounded in the RBV to account for the role of the strategic group level, but uncertainty remains about how to do so. Random coefficients modeling (RCM) provide an appropriate technique to integrate these two levels of analysis, but its use has been limited in strategic management research to date. I review research integrating firm and strategic group levels and provide a roadmap for future research seeking to integrate these two levels’ influences on firm performance, and use RCM to illustrate the effects of firm resources on performance under three depictions of the strategic group level culled from strategic management research. Findings suggest that interpretations about the efficacy of resources’ influence on performance vary considerably across methodological specification. Next, I use RCM to illustrate how strategic management researchers can further integrate the firm and group levels by demonstrating how variables at the group level of analysis may interact with firm-level characteristics. I conclude with suggestions for future research using RCM to integrate the strategic group into multilevel studies predicting firm performance.

Failure mode and effects analysis (FMEA) is a preventive technique in reliability management field. The successful implementation of FMEA technique can avoid or reduce the probability of system failure and achieve good product quality. The FMEA technique had applied in vest scopes which include aerospace, automatic, electronic, mechanic and service industry. The marking process is one of the back ends testing process that is the final process in semiconductor process. The marking process failure can cause bad final product quality and return although is not a primary process. So, how to improve the quality of marking process is one of important production job for semiconductor testing factory. This research firstly implements FMEA technique in laser marking process improvement on semiconductor testing factory and finds out which subsystem has priority failure risk. Secondly, a CCD position solution for priority failure risk subsystem is provided and evaluated. According analysis result, FMEA and CCD position implementation solution for laser marking process improvement can increase yield rate and reduce production cost. Implementation method of this research can provide semiconductor testing factory for reference in laser marking process improvement.

During recent years, the PCB industry has become more aware of the use of analytical test techniques to aid in materials testing. Repeatable quality of base materials, together with the monitoring of the production process and the finished product, has caused supplier and fabricator to consider existing methods and to see whether modern instrument techniques can improve such tests. During meetings such as Internepcon and Productronica, the author has presented developments by DuPont which have used Thermal Analysis techniques to evaluate the materials and processes involved in the manufacture of a multilayer printed circuit board. The purpose of this paper will be to give an up to date review of the work. It will discuss the successes to date and will show where modifications to experimental methods have been made to give more practical data. Specific test methods currently used in the industry will be discussed and recommendations will be made showing Thermal Analysis techniques may offer a more objective test as well as giving the user time savings and a reduction in manpower through increased instrument productivity and versatility.

Customer acquisition and retention methods are the most critical issues for any enterprise. By identifying potential customers and targeting them through marketing activities, enterprises can minimize marketing costs and maximize transaction probability. However, because market surveys are labor- and time-consuming, and data mining is ineffective for obtaining competitor data, enterprises may be unable to understand real-time changes in market trends and consumer preferences. The paper aims to discuss these issues.

This study developed a mechanism that automatically searches for potential customers in virtual communities. In addition, a common product attribute (CPA) model was developed based on the five dimensions of the theory of consumption values and a questionnaire survey was conducted to verify the corresponding relationships. Subsequently, the authors quantified and applied the relationship between the proposed CPA model and consumption values theory.

During the experiment, functional and social values yielded more accurate predictions. Contrary to our expectations, emotional value yielded an inaccurate prediction of potential customers. The overall precision was 0.74, with a threshold of 0.5.

Due to each industry including the distinctive characteristics and attributes regarding its products, the methods and models were only adopted in food industry for testing effectiveness.

Considering the food industry as an example, this study adopted the case study method to screen potential customers based on 400 articles from virtual communities, and combined a latent semantic analysis method with a backpropagation neural network to verify the effectiveness of the proposed method.

By adopting the proposed enterprise-product profile model, enterprises can compile basic information related to their products and industry. The proposed system can be used by enterprises to identify potential customers in areas with potential for market development.